Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
日本語の概要は準備中です。原文の説明を表示しています。
Use when deciding whether a materials result clears Advanced Materials' advance-and-broad-impact gate, or whether it belongs in Advanced Functional Materials, Advanced Science, Small, or Advanced Materials Interfaces. Diagnoses venue fit; does not write or characterize the material.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Advanced Materials publishes across all of materials science — materials chemistry, nanotechnology, energy materials (batteries, photovoltaics, catalysis), electronics and optoelectronics, biomaterials, soft matter, and structural materials. The gate is two tests, AND-ed:
A careful, well-characterized, but incremental result can pass rigor and still fail the gate. That is the most common Adv. Mater. rejection mode, and it is a venue judgment, not a quality judgment.
| Situation | Verdict |
|---|---|
| New material class or design principle + clear cross-field relevance | Adv. Mater. — strong fit |
| New mechanism explaining a property, with general design consequences | Adv. Mater. — strong fit |
| Record device metric driven by a genuinely new material/interface concept | Adv. Mater. — fit (frame the advance) |
| Solid performance gain by established optimization on a known system | Adv. Funct. Mater. (functional focus) |
| Rigorous nanoscale study, well-defined but specialist audience | Small |
| Sound, broad, but best served by gold open access and rapid dissemination | Advanced Science |
| Interface / thin-film / surface study, incremental or specialist | Advanced Materials Interfaces |
| Characterization-only paper with no property or device consequence | Specialist / methods journal |
【Central advance】one sentence (new material / mechanism / property)
【Not incremental because】...
【Broad impact】named out-of-subfield or device audience + why they care
【Design rule / trade-off changed】...
【Verdict】Adv. Mater. strong / Adv. Mater. with impact framing / retarget to AFM / Adv. Sci. / Small / AMI
【Next】advmat-results-framing (if Adv. Mater.) or retarget venue
Scope and portfolio positioning are durable, but article categories and sibling-journal remits evolve — verify on the official Wiley Advanced Materials author page.
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概要と使いどころ
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
日本語の概要は準備中です。原文の説明を表示しています。
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
日本語の概要は準備中です。原文の説明を表示しています。
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
日本語の概要は準備中です。原文の説明を表示しています。
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
日本語の概要は準備中です。原文の説明を表示しています。
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
日本語の概要は準備中です。原文の説明を表示しています。